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I use the files from the "Download Processed Images" (the tar file).
To me it seems that the images become sorted using MiniImageNetDataLoader, and the first images for each label are simpler to classify than later ones?
If I use shuffle = True
at the end of the middle line (there are three occurrences of such lines)
random.shuffle(sampled_character_folders)
labels_and_images = self.get_images(sampled_character_folders, range(self.way_num), nb_samples=self.num_samples_per_class, shuffle=False)
labels = [li[0] for li in labels_and_images]
it is much more difficult to train the data.
I got suspicious because the default in
def get_images(self, paths, labels, nb_samples=None, shuffle=True):
which is overwritten in the call.
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